Question 1
(a)
Explain various types of metadata in data warehouse.
3 Marks
(b)
Give the benefits of data warehousing.
4 Marks
(c)
What is cuboid? Explain following OLAP Operations with examples.
1)drill down
2)roll up
3)slice
4)dice
7 Marks
Gujarat Technological UniversitySummer 2026 Examination
GTU 3161610 Data Warehousing and Mining Summer 2026 Paper Solution & PDF
B.E. · IT Engineering · Semester 6 · Subject Code: 3161610
Total Marks70 MarksExternal theory exam
Passing Marks23 Marks33% minimum cutoff
Exam Duration2.5 Hours10:30 AM – 1:00 PM
Paper Structure5 QuestionsWith internal OR choices
Question 2
(a)
Differentiate OLAP and OLTP
3 Marks
(b)
What is data mining? What are the major challenges of mining huge amount of data?
4 Marks
(c)
Draw and explain data warehouse architecture.
7 Marks
OR OPTION
(c)
Explain the various stage of KDD process.
7 Marks
Question 3
(a)
Write importance of preprocessing in data mining.
3 Marks
(b)
Explain different types of data on which mining can be performed.
4 Marks
(c)
Explain various schema for multidimensional database.
7 Marks
OR OPTION
(a)
Give the importance of dimensionality reduction.
3 Marks
(b)
What is normalization? Explain min-max normalization with suitable example.
4 Marks
(c)
Explain data smoothing methods to divide given data into bins of size 3 by bin means, by bin medians and by bin boundaries. Consider the data: 10, 2, 19, 18, 20, 18, 25, 28, 22
7 Marks
Question 4
(a)
Differentiate Fact table vs. Dimension table.
3 Marks
(b)
Explain support and confidence with example.
4 Marks
(c)
Find frequent item-sets and association rules using Apriori algorithm on the following data set with minimum support count is 2 and minimum confidence is 75%. Sr. No TID List of items 1 T1 A,B,E 2 T2 B,D 3 T3 B,C 4 T4 A,B,D 5 T5 A,C 6 T6 B,C 7 T7 A,C 8 T8 A,B,C,E 9 T9 A,B,C
7 Marks
OR OPTION
(a)
Differentiate supervised and unsupervised learning.
3 Marks
(b)
Explain various issues of classification.
4 Marks
(c)
Explain Information Gain, Gain Ratio, Gini Index
7 Marks
Question 5
(a)
Give differences between linear and logistic regression.
3 Marks
(b)
What is outlier? Discuss different methods for outlier detection.
4 Marks
(c)
Explain k-means clustering algorithm.
7 Marks
OR OPTION
(a)
Give the differences between Spatial and Temporal Data Mining.
3 Marks
(b)
Write short note on text mining.
4 Marks
(c)
What is web mining? Explain types of web mining. ---------------------- .
7 Marks
College Exam Groups
Studying for Data Warehousing and Mining?
Circulate this solved paper with KaTeX formulas and 1-click AI step solvers to your batchmates on WhatsApp or Telegram.
About this Examination Paper & Attribution
Official Gujarat Technological University (GTU) examination paper and step-by-step solutions for Data Warehousing and Mining (Summer 2026, B.E. · IT Engineering, Sem 6). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.
Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.